Mobile health (mHealth) is considered one of the most transformative drivers for health informatics delivery of ubiquitous medical applications. Machine learning has proven to be a powerful tool in classifying medical images for detecting various diseases. However, supervised machine learning requires a large amount of data to train the model, whose storage and processing pose considerable system requirements challenges for mobile applications. Therefore, many studies focus on…

I have been frequently asked about the tools for the Machine Learnign projects There are lot of them on the market so in my newest post you will find my view on them. I would like to start my first Machine Learning project. But I do not have tools. What should I do? What are the tools I could use?

I will give you some hints and advices based on the toolbox I use. Of course there are more great tools but you should pick the ones you like. You should also use the tools that make your…

I have mentioned that every Machine Learning process is built from several steps like:

• what would you like to achieve (define the goal)
• prepare the data
• select an algorithm(s)
• build and train the model
• test the model (and score it)

Let’s review them one by one. I should mention that you will be able to find information over the internet that the number of steps is different from what you see on this blog. For example you can…

What is Machine Learning? This story started in mid 60 in the last century. Scientists and engineers found a lot of problems that were too complicated for traditional algorithms that it was not possible to create a program that could have possibly solved the problem.

Imagine a case where you have an object that is descirbed by 21 properties (as an input) and based on these properties you need to classify it to group A or to the group B. How would you solve the problem? Would you need…

As we all know that artificial Intelligence is slowly slowly becoming the most important and most integral part for the small to big businesses. It helps the business from the purchase of a product or manufactures the products to deliver the product to the client or customers. Here we have come with a small analysis of big business Company named coca…

The internet is evolving day by day, and when users shop online, they are flooded with thousands of results, leaving them in a dilemma to choose the best possible product that suits their requirements. Have you ever thought of how Google Ads precisely knew what you need and display…

When we look at broadly different kinds of Machine Learning that are used in practice in Artificial Intelligence

Historically, there have been several approaches in Machine learning for AI like supervised learning, unsupervised learning, reinforcement learning, case-based reasoning, inductive logic programming, experience based generalisation etc. there have been several examples of waves of machine learning for different AI problems. But, of them the 3 most important categories of…

AI is a new buzzword but there has been a lot of talk around analytics and prospects over a decade. Here we present a perspective that AI is a continuum of Analytics

Let us see how...

Different approaches in Data Science and analytics have been originated in the field of statistics.

AI has emerged on the other hand out of computer science as a practice and science of studying "intelligent agents". 

The way is to treat AI as extending conventional analytics with a…

A complete guide to K-means clustering algorithm

Everything you need to know about a top algorithm in Machine Learning

Introduction:

When dealing with building machine learning models, Data scientists spend most of the time on 2 main tasks when building machine learning models

Pre-processing and Cleaning

The major portion of time goes in to collecting, understanding, and analysing, cleaning the data and then building features. All the above steps mentioned are very important and critical to build successful machine learning…

Price errors and their impact:



Price errors are one of the ways in which revenue leakage occurs in e-commerce business. Although retailers put various checks and balances in place, pricing errors are still common. Data entry mistakes, misplaced decimal points, reversal of digits, and other clerical errors made in hurry are the major contributors. It can also occur because errors in feeding promotional offer dates. Promotions might unintendedly start early or end late. Such revenue…

What is Automated Machine Learning? Quite simply, it is the means by which your business can optimize resources, encourage collaboration and rapidly and dependably distribute data across the enterprise and use that data to predict, plan and achieve revenue goals.

With the right tools, today’s average business user can become a Citizen Data Scientist, using data integrated from various sources to learn, test theories and make decisions. AutoML comes into play as…

Summary: The Gartner Magic Quadrant for Data Science and Machine Learning Platforms is just out and once again there are big changes in the leaderboard.  Some major incumbents have fallen and some new challengers have emerged.

The Gartner Magic Quadrant for Data Science and Machine Learning Platforms is just out and once again there are big changes in the leaderboard.  Say what you will about our profession but as a platform developer you…

October is historically the most volatile month for stocks, but is this a persistent signal or just noise in the data?

Stocks, Significance Testing & p-Hacking. Follow me on Twitter (twitter.com/pdquant) for more. Over the past 32 years, October has been the most volatile month on average for the S&P500 and December the least, in this article we will use simulation to assess the…

How machines process and understand human language

Everything we express (either verbally or in written) carries huge amounts of information. The topic we choose, our tone, our selection of words, everything adds some type of information that can be interpreted and value extracted from it. In theory, we can understand and even predict human behaviour using that information.…

Machine learning is the branch of computer science and a subfield of Artificial Intelligence that utilizes past data to learn from and use its knowledge to make future decisions. Machine learning is at the intersection of computer science, engineering, and statistics. The goal of machine learning is to generalize a detectable pattern or to create an unknown rule from given examples.



Machine learning is broadly classified into three categories but nonetheless, based on the…

An important principle of data science is that data mining is a process. It includes the application of information technology, such as the automated discovery and evaluation of patterns from data. It also includes an analyst’s creativity, business knowledge, and common sense. Understanding the whole process helps to structure data mining projects.

Since the data mining process breaks up the overall task…

                                                                                                  Source: www.mstecker.com/…

Artificial Intelligence and Machine Learning are two terms related to the world of computer science that can be heard a lot these days. These technologies are helping to bring about a considerable change in different fields today. Be it medical sciences, meteorology, robotics, understanding customer perspectives or scientific developments; these fields are offering an excellent way to move forward without letting technology stagnate.…